The New Waydev
Engineering intelligence platform that attributes AI-generated code to specific agents and measures AI ROI against DORA, SPACE, and DX metrics.
If AI coding assistants are a real line item in your budget and nobody can say what they returned, Waydev's per-agent attribution plus AI Adoption, AI Impact, and AI ROI tracking is a direct answer rather than another DORA board with a new tab. The G2 software engineering intelligence market-leader placements and Fortune 500 customer stories suggest it holds up in enterprise procurement, and the Waydev Agent natural-language layer saves an engineering manager from writing queries. It is heavier than a 40-engineer team needs, and annual-per-active-contributor billing means you should size seats carefully. Buy it as AI spend accountability, and compare it against Jellyfish and LinearB on
Verified 13d ago · liveness 72/100 · cite: rightaichoice.com/tools/the-new-waydev
- Engineering leaders at 100+ engineer orgs running multiple AI coding agents and needing per-agent output data
- CTOs who must show the board what AI coding tool spend actually returned in delivery terms
- FinOps and R&D finance teams that need cost per PR and automated cost capitalization from engineering data
- Platform teams standardizing on a single AI assistant and comparing candidates on real production outcomes
- Teams not using AI code generation — you'd pay for governance over a problem that doesn't exist
- Organizations without Git-based repositories and CI pipelines to pull data from
- Managers who only want individual developer productivity views with no AI or finance angle
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Skip Waydev if your engineers are not yet using AI coding agents inside Git-based repositories, because the AI Adoption, Impact, and ROI modules have nothing to attribute and you would be paying enterprise prices for delivery metrics alone.
Billing is annual per active contributor, so contractors and rotating staff can inflate the seat count you commit to at renewal.
Waydev prices annually per active contributor and sells to enterprise engineering orgs, so it is a budget line comparable to Jellyfish and LinearB rather than to lighter tools like Swarmia. A 50-engineer team will feel the per-contributor cost sharply; a 500-engineer org gets the AI ROI and cost-capitalization reporting amortized across far more seats, which is where the platform's economics make the most sense.
In short
The New Waydev — Engineering intelligence platform that attributes AI-generated code to specific agents and measures AI ROI against DORA, SPACE, and DX metrics. Best for Engineering leaders at 100+ engineer orgs running multiple AI coding agents and needing per-agent output data, CTOs who must show the board what AI coding tool spend actually returned in delivery terms, FinOps and R&D finance teams that need cost per PR and automated cost capitalization from engineering data. Contact Sales pricing.
What's new in The New Waydev
Checked 6 days agoAcross the latest 1 update: 1 news mention.
What people actually say about The New Waydev — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
21 mentions across 2 sources (YouTube, Product Hunt) · researched Aug 16, 2026.
Average across the 2 sources that answered — each source counts once, not each post.
- +Per-agent AI code attribution fills a real gap — teams finally see which tool (Copilot, Cursor, Claude) writes what ships.
- +Cost per shipped PR is a killer metric for justifying AI spend to finance.
- +Focus on outcomes (deployment status, acceptance rate) over vanity counts wins praise.
- +Integrates with major tools (GitHub, GitLab, Jira, Slack) out of the box.
- +Ties AI code activity to broader DORA metrics and cycle time — comprehensive view.
- −No real user reviews yet — all buzz is from launch, not long-term usage.
- −Attribution accuracy when PRs mix multiple agents + human edits is unclear — a key unanswered question.
- −Risk of metric gaming (PR splitting) if used as a performance scorecard without careful rollout.
- −Advanced skill level means setup and interpretation may be heavy for small teams.
- −Pricing unclear in public data — hidden costs or enterprise-only tiers could deter SMBs.
- • No public pricing on the site — enterprise sales inquiry only
- • Potential per-seat costs that scale with team size
- • Setup and onboarding might require paid professional services
Viability Score
How well maintained and how widely used is The New Waydev? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Per-agent AI code attribution across GitHub Copilot, Cursor, and Claude Code
- AI Adoption tracking for how many engineers use AI coding agents
- AI Impact tracking with AI agents continuously following progress
- AI ROI tracking with AI Coach delivering recommendations
- Waydev Agent for natural-language queries about predicted delivery outcomes
- DORA metrics: deployment frequency, lead time, change failure rate, MTTR
- Cycle time analysis from first commit to production release
- Pull request insights and merge quality reporting
- Sprint velocity, sprint commitment, and risk tracking
- Developer Experience (DX) insights into team challenges
- Benchmarking of team performance against company averages
- PR hygiene overview of linked and unlinked pull requests
- Studio custom dashboards, custom metrics with formulas, and custom reports
- Resource planning, project costs, resource allocation, and cost capitalization
- Automatic targets and milestone notifications
About The New Waydev
Waydev is an engineering intelligence platform built for one question most CTOs still can't answer: did the money spent on AI coding agents actually change what shipped? It sits on your Git and CI data and attributes AI-generated code to specific agents — GitHub Copilot, Cursor, and Claude Code are named on the platform — then lines those measurements up against DORA, SPACE, and DX metrics so leaders can compare agent output to real deployment outcomes instead of quarterly guesswork. The newest muscle is on the automation side. AI Adoption tracks how many engineers actually use agents. AI Impact has AI agents continuously following progress. AI ROI pairs with the AI Coach to surface recommendations rather than another dashboard, and Waydev Agent answers natural-language questions about predicted outcomes. Alongside that you get DORA metrics, cycle time from first commit to production release, pull request insights, velocity and sprint risk, merge quality reports, sprint commitment, health insights, benchmarking, and PR hygiene across linked and unlinked pull requests. For organizations where engineering spend shows up in a finance conversation, Waydev covers resource planning, project costs, resource allocation, and automated cost capitalization — the bridge between engineering and R&D accounting. Studio lets teams build custom dashboards, custom formulas for metrics, and complex reports off any Waydev metric, with targets and milestone notifications on top. Integrations pull from GitHub, GitLab, Bitbucket, Jira, Slack, CircleCI, Jenkins, GitHub Actions, GitLab CI, and Azure DevOps. Waydev positions itself as engineering intelligence on autopilot, publishes comparison pages against Jellyfish, LinearB, Swarmia, and DX, and markets heavily to enterprise engineering orgs — TATA Health, Citi Ventures, and Sovos appear in its customer stories. Billing is annual per active contributor, so model the seat count before you commit.
Behind the Verdict
The problem Waydev solves is unusually well defined. Most engineering intelligence tools were built to measure human delivery, then bolted on an AI tab when assistants got popular. Waydev built the AI layer as the headline: AI Adoption tells you how many engineers actually use agents, AI Impact has AI agents continuously following progress, and AI ROI pairs with the AI Coach to turn that into recommendations. The per-agent attribution across GitHub Copilot, Cursor, and Claude Code is the differentiator — it lets you ask which agent produces code that reaches production, and what that code costs per shipped pull request. Strengths. The measurement surface is broad and internally consistent: DORA, SPACE, DX, cycle time, pull request insights, velocity and sprint risk, merge quality, sprint commitment, benchmarking against company averages, and PR hygiene for linked and unlinked pulls all live in the same data model, which matters because AI attribution is only credible if the delivery metrics beside it are the ones finance and the board already trust. Studio is the underrated piece — custom dashboards, custom formulas, and custom reports off any Waydev metric mean you are not stuck with the vendor's definition of a metric. Cost capitalization and resource planning give the platform a genuine second buyer inside the company, the R&D finance team, which is rare for tools in this category. Weaknesses and open questions. Waydev is priced annually per active contributor, so a large org with rotating contractors can watch seats add up; define "active contributor" early. The product is deep, which means onboarding effort — you are connecting Git and CI providers and letting the system backfill before the AI ROI numbers mean anything, and the first month is groundwork rather than insight. As with any attribution system, the output is only as good as the tagging: if your teams mix agents or generate code outside tracked repositories, the attribution degrades. And the platform is genuinely overkill if your team is not using AI code generation at all, because you would be paying for governance over a problem you do not have. The competitive read is straightforward. Compared with Jellyfish, Waydev leans harder into AI-specific attribution and cost capitalization; compared with LinearB, it is less about workflow automation and more about measurement and reporting; compared with Swarmia and DX, the AI ROI and finance angles are the separation. None of those comparisons should be settled by a marketing page — run all of them against the same two sprints of your own data. Where it fits: 100+ engineer organizations running multiple AI coding agents, CTOs who must show the board what AI tool spend returned in delivery terms, and FinOps or R&D finance teams that need cost per PR and automated capitalization. Where it does not: teams without Git-based repositories and CI pipelines to pull from, and managers who only want individual developer productivity views
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Real-world workflow fit
Concrete scenarios for the personas The New Waydev actually fits — and what changes day-one when you adopt it.
Connect GitHub, GitLab, and your CI providers to Waydev, then let AI Adoption, AI Impact, and AI ROI backfill a full quarter so per-agent attribution has real history behind it.
Outcome: A board-ready answer on what each AI coding agent returned in shipped code, plus cost per PR that finance can put next to the subscription line.
Ask Waydev Agent about predicted delivery outcomes for a sprint instead of writing a query, then drop the resulting report into Studio as a custom dashboard you check each Monday.
Outcome: Earlier warning on sprint risk and merge quality issues, and a repeatable view your team reviews without a data analyst in the loop.
Wire resource planning, project costs, and resource allocation into the same Waydev metrics the engineering org already uses, and automate capitalization reporting from that data.
Outcome: Cost capitalization reports generated from engineering activity rather than assembled by hand, with the AI tooling spend included in the same picture.
Use Cases
- Track which AI agent generates the highest quality code that reaches production
- Calculate cost per shipped PR to justify Copilot, Cursor, or Claude Code subscriptions
- Compare acceptance rates of AI-generated code across teams and repos
- Identify bottlenecks where AI code fails deployment and reduce rework
- Benchmark engineering velocity against industry DORA metrics with AI attribution
- Generate automated reports for finance on R&D cost capitalization from AI tools
- Answer delivery-risk questions in plain English through Waydev Agent
- Build custom dashboards and formulas for metrics your leadership actually reviews
Models Under the Hood
as of 2026-09-14
Limitations
- Waydev measures engineering delivery and AI agent impact, so it requires Git-based repositories and connected CI pipelines before any number it shows is meaningful; without that data there is nothing to attribute.
- The AI outputs depend on agents generating code inside tracked repositories, so mixed or untracked agent usage degrades the attribution.
- The platform is deep enough that the first weeks are connection and backfill work rather than insight, and it is aimed at organizations with a real AI tooling line item — smaller teams without AI agents get little from the AI Adoption, Impact, and ROI modules.
as of 2026-09-24
Verification history
We have re-verified The New Waydev 9 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
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Showing the 6 most recent of 9 verification passes.
Free to cite with attribution — this page re-verifies continuously.
Where the pricing makes sense
The company stage and team size where The New Waydev's pricing actually pencils out — and where peers do it cheaper.
Waydev prices annually per active contributor and sells to enterprise engineering orgs, so it is a budget line comparable to Jellyfish and LinearB rather than to lighter tools like Swarmia. A 50-engineer team will feel the per-contributor cost sharply; a 500-engineer org gets the AI ROI and cost-capitalization reporting amortized across far more seats, which is where the platform's economics make the most sense.
Setup time & first value
How long it actually takes to get something useful out of The New Waydev — broken out by persona, not the marketing-page minute.
Expect a multi-week ramp rather than a same-day win. Connecting source control, CI, and ticketing sources and letting Waydev backfill delivery history is the first milestone; AI Adoption, Impact, and ROI reporting only becomes trustworthy after that history exists. A single connected organization can reach first useful DORA and cycle time views quickly, while a multi-repo enterprise with several
Switching to or from The New Waydev
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Jellyfish: connect the same Git, CI, and Jira sources in Waydev, then rebuild your key leadership dashboards in Studio using Waydev metrics.
- →From LinearB: port your delivery and cycle time reporting into Waydev's DORA and cycle time views, then add AI agent attribution on top.
- →From Swarmia: recreate your DX and sprint reporting in Waydev, then extend it with AI Adoption, AI Impact, and AI ROI.
- →From spreadsheets: stop hand-assembling DORA and cost capitalization figures and let Waydev pull them from connected repositories and CI.
- ↗To Jellyfish: export your Waydev dashboards and metric definitions, then map Waydev DORA and cycle time views onto Jellyfish's reporting model.
- ↗To LinearB: carry over delivery and pull request reporting, and rebuild AI agent attribution outside Waydev if you still need it.
- ↗To Swarmia: move your DX and sprint reporting across, and accept that per-agent AI cost attribution may not follow.
- ↗To in-house reporting: pull engineering data directly from Git and CI and rebuild the DORA and cycle time views yourself.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “The New Waydev”, and we withheld 6: 6 did not mention The New Waydev. We are showing none, because we could not prove any of them are about The New Waydev.
Official links
Tools that pair well with The New Waydev
Common stack mates teams adopt alongside The New Waydev, with the specific reason each pairing earns its keep.
Bito
Bito Governor is an AI model router and code context engine that grounds coding agents in your codebase to cut agent spend 40-70%
Quadratic
Quadratic is an AI spreadsheet where the grid runs Python, SQL, JavaScript, and formulas against live data sources.
Moderne
Moderne is a deterministic code-change layer that sequences repositories into a Lossless Semantic Tree so transformations land identically everywhere.
Featured Head-to-Head Comparisons
The New Waydev vs Persefoni
These tools are not direct competitors: Waydev is for engineering leaders tracking AI coding ROI, while Persefoni is for sustainability teams managing carbon compliance. Choose Waydev if your priority is measuring AI-generated code value; choose Persefoni if you need regulatory-grade carbon accounting. For a combined stack, both can coexist.
The New Waydev vs Nectar Energy
Choose Nectar Energy if you manage commercial building energy use and need automated HVAC/lighting control plus ESG reporting; choose The New Waydev if you lead engineering teams using AI coding assistants and need per-agent ROI and DORA metrics. These tools address completely different domains—there is no direct competition.
The New Waydev vs Cognition Ai
If you're an engineering leader needing to justify AI tool spend by tracking exactly which agent (Copilot, Cursor, Claude Code) produces what code, at what cost, and how often it ships to production, Waydev is purpose-built for that. If you need an autonomous agent that plans, codes, and ships entire features without hand-holding, Devin is a better fit — especially with its new FrontierCode eval and $10M productivity guarantee. Waydev is a measurement tool; Devin is a doer.
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